[eng] The ocean, a vast expanse that far surpasses the terrestrial environment, has emerged as a critical frontier for exploration. This has led to the increasing use of multi-robot systems (MRS) to survey ever larger areas of the ocean. However, the underwater environment presents unique challenges for MRS coordination due to severe communication constraints. These constraints arise from the inherent properties of ocean acoustics, including latency, signal attenuation, multipath propagation and limited bandwidth, which significantly affect the communication between robots. Effective communication is essential in any MRS to enable robots to share data and coordinate their actions towards a common goal. To address these challenges, we present a novel MRS coordination algorithm tailored for ocean applications. The MRS is composed of an Autonomous Underwater Vehicles fleet and an Autonomous Surface Vehicle. The algorithm uses characterizations of acoustic communication signals as inputs in the decision-making process to determine which vehicle should be assigned for data collection, thereby improving information transmission during oceanographic exploration missions. By exploiting the characteristics of the acoustic communication channel, the algorithm aims to maximise the overall group utility while taking into account the constraints of ocean acoustics. Several realistic simulation experiments have been conducted to evaluate the proposed system. The results demonstrate the robustness and effectiveness of the algorithm in improving coordination and mission success in underwater environments, highlighting its potential to overcome the unique challenges of the marine domain.